3-D machine vision systems utilize a number of different schemes such as range finding, structured light and binocular vision to see in three dimensions. Range finding and structured light schemes are typically the easiest to implement. Both techniques rely for depth cues on the way light or other radiation such as sound waves reflect from the surface of an object. Range finding systems typically time the reflection of the laser beam to the object and back again to measure its distance--similar to radar.
Structured light systems project light in a controlled manner on the object. The system then determines the distance to the object by triangulation and deduces the object's shape from the pattern formed by the intersection of the object's surface with the beam of light.
The use of structured, point source, coherent or other types of specialized lighting is fundamental to much of the prior art. For example, such specialized lighting is disclosed in the U.S. Pat. Nos. to Kremers et al 4,412,121 and Haefner et al 4,675,502.
Binocular vision systems utilize two cameras and employ the same general approach as that used in human vision (i.e. binocular parallax). The slight disparity between the two views of the same scene is used as a depth cue, i.e. the greater the parallax the closer the object.
One problem associated with the development of a practical machine vision system based on binocular parallax is the "correspondence" problem. That is, objects in each view must match with one another before the disparity between the two views can be determined. Matching can be a problem because, as a result of the parallax, an object may appear slightly differently in the right and left views and may be partially or totally obscured in one view.
3-D vision systems which rely on the range finding or structured light schemes are also inherently limited because they require interaction with the object under observation. These systems may be adequate for many applications. However, a vision system should be passive to avoid putting constraints on the observed objects or their environment.
The U.S. Pat. Nos. to Egli et al., 4,672,562 and Hay et al, 4,238,828 require the use of non-coplanar targets on an object which constrain the type of observed objects which can be viewed by the systems disclosed.
The paper entitled "New Methods For Matching 3-D Objects With Single Perspective Views" authored by Horaud and which appeared in the IEEE Transactions 0n Pattern Analysis And Machine Intelligence, Vol. PAMI-9, May 1987, pages 401-412, discloses a computer vision system which derives properties of the 3-D physical world from viewing 2-D images. A model-based interpretation of a single perspective image is performed. Image linear features and linear feature sets are back-projected onto a 2-D plane of 3-D space and geometric models are then used for selecting possible solutions. In general, the paper describes a computationally intensive method of interpreting the back-projections of the three dimensional scenes onto the 2-D plane.
Other related vision methods and systems are disclosed in the U.S. Pat. Nos. to Kano, 4,099,880; Dimatteo et al., 4,402,608 and Ruott, Jr. 3,986,007.